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Mining and data in 2017 Pt 1

Mining and data in 2017 Pt 1

We speak with Ashley Bosworth, Director of Analytics and Innovation at Pulse Mining on the year ahead for the mining industry:

What do you think will be the biggest change in the mining industry in 2017?

In terms of the political landscape 2017 is shaping up to be one of the most volatile years in decades. This volatility has the potential to impact mining markets in a major way, particularly where China is involved, be it as a consumer/importer of commodities such as coal and iron ore, or as an exporter of rare earth minerals.

Seaborne market susceptibility to Chinese regulatory change for coal and energy production was definitively demonstrated in 2016, and from 2017 onwards this situation has the potential to be amplified through the possibility of a trade war with the USA (if President Trump’s rhetoric becomes reality).

Further disruption to international markets is possible if the US can re-enter the coal export market in any significant fashion. For instance, if President Trump is somehow able to clear existing state impediments to Powder River Basin coal reaching Pacific coast ports, the shipping of thermal coal at approx. $US 10/short ton would prove to be a huge disruptor to the current global seaborne market.

All of this leads us at Pulse Mining to believe that the biggest change in the mining industry in 2017 will not be from uptake of automated vehicles or other technological innovation in the hardware/machinery space, or indeed changes in work practices, but in the rate of development and uptake of predictive analytics and scenario planning to enable miners to become much more agile in the marketplace.

Several other changes will necessarily support the rise of predictive analytics, including increased:

Sharing of data across systems (including between machines via IoT)

Digitisation, which will significantly decrease the need for data entry

Real-time reporting against performance metrics and KPI’s

Ability to intervene in real-time to improve performance.

What sectors in mining are growing, and which ones are at risk?

As previously noted, the immediate market future of bulk commodities such as coal and iron ore is largely dependent on Chinese demand and regulation/legislation. In the longer term developing markets in Asia may take up some of the slack as China reduces demand.

In volatile times demand for gold, diamonds and other ‘haven’ commodities will potentially rise as a form of safety net for investors, as it has done during times of recession in the past. There is also potential for demand for commodities and minerals used in high-tech manufacture to continue to grow, particularly the rarer minerals – e.g. tungsten, antimony, bismuth, molybdenum, strontium. It should be noted that China is currently the leading producer of all these.

What role will analytics play in companies during 2017?

Analytics will play an enormously significant role in mining companies during 2017 in two main areas:

Embedding predictive analytics and scenario planning in BAU (business as usual) processes to enable miners to become much more agile in the marketplace

Enabling operational excellence – this remains important, particularly in terms of improving productivity and was the number 1 trend for 2016 identified by Deloitte in their Tracking the Trends 2016 report.

Will more employees in the mining sector start using data in their daily lives?

Definitely – this is already happening. Data (and analytics) usage will become ‘common place’ right across the mining landscape, from production at the pit to shipping from the port.

As in other industries, we are increasingly seeing demand for analytics, and to a lesser extent data entry, on mobile devices, together with data mash-up from multiple sources (business systems, machinery, localised systems, etc.).

How close to the “coal face” will data get, and how much difference will it make to day-to-day activities?

Data is already right at the ‘coal face’ – mining machinery such as continuous miners are fitted with hundreds of sensors that capture and transmit data continuously. The changes that are happening are more around the timeliness of using such data, than its availability. For instance, many companies currently only view the machine data (in the form of OEM reports (Original Equipment Manufacturer) daily... this does not allow for on-the-fly adjustments to production to be made.

Pulse Mining is moving beyond the limits of the OEM reports. Connectivity via IoT now means that this data can be collated and analysed, combined with data from other relevant sources, and presented either in real-time on a mobile device or emailed to stakeholders in accordance with a pre-determined schedule.